New insights into the origin of remote PPG signals in visible light and infrared

Intraoperative Imaging of Cortical Blood Flow by Camera-Based Photoplethysmography at Green Light

Intraoperative evaluation of blood perfusion in the brain cortex is an important but hitherto unresolved problem. Our aim was to demonstrate the feasibility of cerebral microcirculation assessment during open brain surgery by using camera-based photoplethysmography (cbPPG) synchronized with an electrocardiograph. Cortical blood flow was monitored in five patients with different diagnoses. Two cases (tumor resection and extra-intracranial bypass grafting) are presented in detail. Blood-flow parameters were visualized after processing cortex images recorded under green-light illumination before and after surgical intervention. In all cases, blood flow was successfully visualized in >95% of open brain. Distributions of blood pulsation amplitude, a parameter related to cortical blood perfusion; pulse arrival time; and blood-pressure-pulse shape were calculated with high spatial resolution (in every pixel). Changes in cerebral blood supply caused by surgical intervention were clearly revealed. We have shown that the temporal spread of pulse arrival time and the spatiotemporal variability of pulse shape are very sensitive markers of brain circulatory disturbances. The green-light cbPPG system offers a new approach to objective assessment of blood-flow changes in the brain during surgical intervention. The proposed system allows for contactless monitoring of cortex blood flow in real time with high resolution, thus providing useful information for surgery optimization and minimization of brain tissue damage.

Investigating the origin of photoplethysmography using a multiwavelength Monte Carlo model

Photoplethysmography (PPG) is a photometric technique used for the measurement of volumetric changes in the blood. The recent interest in new applications of PPG has invigorated more fundamental research regarding the origin of the PPG waveform, which since its discovery in 1937, remains inconclusive. A handful of studies in the recent past have explored various hypotheses for the origin of PPG. These studies relate PPG to mechanical movement, red blood cell orientation or blood volume variations.

OBJECTIVE

Recognising the significance and need to corroborate a theory behind PPG formation, the present work rigorously investigates the origin of PPG based on a realistic model of light-tissue interactions.

APPROACH

A three-dimensional comprehensive Monte Carlo model of finger-PPG was developed and explored to quantify the optical entities pertinent to PPG (e.g. absorbance, reflectance, and penetration depth) as the functions of multiple wavelengths and source-detector separations. Complementary to the simulations, a pilot in vivo investigation was conducted on eight healthy volunteers. PPG signals were recorded using a custom-made multiwavelength sensor with an adjustable source-detector separation.

MAIN RESULTS

Simulated results illustrate the distribution of photon-tissue interactions in the reflectance PPG geometry. The depth-selective analysis quantifies the contributions of the dermal and subdermal tissue layers in the PPG wave formation. A strong negative correlation (r = -0.96) is found between the ratios of the simulated absorbances and measured PPG amplitudes.

SIGNIFICANCE

This work quantified for the first time the contributions of different tissue layers and sublayers in the formation of the PPG signal.

Impact of makeup on remote-PPG monitoring

Camera-based remote photoplethysmography (remote-PPG) enables contactless measurement of blood volume pulse from the human skin. Skin visibility is essential to remote-PPG as the camera needs to capture the light reflected from the skin that penetrates deep into skin tissues and carries blood pulsation information. The use of facial makeup may jeopardize this measurement by reducing the amount of light penetrating into and reflecting from the skin. In this paper, we conduct an empirical study to thoroughly investigate the impact of makeup on remote-PPG monitoring, in both the visible (RGB) and invisible (Near Infrared, NIR) lighting conditions. The experiment shows that makeup has negative influence on remote-PPG, which reduces the relative PPG strength (AC/DC) at different wavelengths and changes the normalized PPG signature across multiple wavelengths. It makes (i) the pulse-rate extraction more difficult in both the RGB and NIR, although NIR is less affected than RGB, and (ii) the blood oxygen saturation extraction in NIR impossible. To the best of our knowledge, this is the first work that systematically investigate the impact of makeup on camera-based remote-PPG monitoring.

Pulse oximetry based on photoplethysmography imaging with red and green light : Calibratability and challenges

Remotely measuring the arterial blood oxygen saturation (SpO₂) in visible light (Vis) involves different probing depths, which may compromise calibratibility. This paper assesses the feasibility of calibrating camera-based SpO₂ (SpO_2,cam) using red and green light. Camera-based photoplethysmographic (PPG) signals were measured at 46 healthy adults at center wavelengths of 580 nm (green), 675 nm (red), and 840 nm (near-infrared; NIR). Subjects had their faces recorded during normoxia and hypoxia and under gradual cooling. SpO_2,cam estimates in Vis were based on the normalized ratio of camera-based PPG amplitudes in red over green light (RoG). SpO_2,cam in Vis was validated against contact SpO₂ (reference) and compared with SpO_2,cam estimated using red-NIR wavelengths. An RoG-based calibration curve for SpO₂ was determined based on data with a SpO₂ range of 85-100%. We found an [Formula: see text] error of 2.9% (higher than the [Formula: see text] for SpO_2,cam in red-NIR). Additional measurements on normoxic subjects under temperature cooling (from [Formula: see text] to [Formula: see text]) evidenced a significant bias of - 1.7, CI [- 2.7, - 0.7]%. It was also noted that SpO[Formula: see text] estimated at the cheeks was significantly biased (- 3.6, CI [- 5.7, - 1.5]%) with respect to forehead estimations. Under controlled conditions, SpO[Formula: see text] can be calibrated with red and green light but the accuracy is less than that of SpO[Formula: see text] estimated in the usual red-NIR window.

Influence of blood pulsation on diagnostic volume in pulse oximetry and photoplethysmography measurements

Recent advances in the development of ultra-compact semiconductor lasers and technology of printed flexible hybrid electronics have opened broad perspectives for the design of new pulse oximetry and photoplethysmography devices. Conceptual design of optical diagnostic devices requires careful selection of various technical parameters, including spectral range; polarization and intensity of incident light; actual size, geometry, and sensitivity of the detector; and mutual position of the source and detector on the surface of skin. In the current study utilizing a unified Monte Carlo computational tool, we explore the variations in diagnostic volume due to arterial blood pulsation for typical transmitted and back-scattered probing configurations in a human finger. The results of computational studies show that the variations in diagnostic volumes due to arterial pulse wave are notably (up to 45%) different in visible and near-infrared spectral ranges in both transmitted and back-scattered probing geometries. While these variations are acceptable for relative measurements in pulse oximetry and/or photoplethysmography, for absolute measurements, an alignment normalization of diagnostic volume is required and can be done by a computational approach utilized in the framework of the current study.

A Broader Look: Camera-Based Vital Sign Estimation across the Spectrum

OBJECTIVES

Camera-based vital sign estimation allows the contactless assessment of important physiological parameters. Seminal contributions were made in the 1930s, 1980s, and 2000s, and the speed of development seems ever increasing. In this suivey, we aim to overview the most recent works in this area, describe their common features as well as shortcomings, and highlight interesting "outliers".

METHODS

We performed a comprehensive literature research and quantitative analysis of papers published between 2016 and 2018. Quantitative information about the number of subjects, studies with healthy volunteers vs. pathological conditions, public datasets, laboratory vs. real-world works, types of camera, usage of machine learning, and spectral properties of data was extracted. Moreover, a qualitative analysis of illumination used and recent advantages in terms of algorithmic developments was also performed.

RESULTS

Since 2016, 116 papers were published on camera-based vital sign estimation and 59% of papers presented results on 20 or fewer subjects. While the average number of participants increased from 15.7 in 2016 to 22.9 in 2018, the vast majority of papers (n=100) were on healthy subjects. Four public datasets were used in 10 publications. We found 27 papers whose application scenario could be considered a real-world use case, such as monitoring during exercise or driving. These include 16 papers that dealt with non-healthy subjects. The majority of papers (n=61) presented results based on visual, red-green-blue (RGB) information, followed by RGB combined with other parts of the electromagnetic spectrum (n=18), and thermography only (n=12), while other works (n=25) used other mono- or polychromatic non-RGB data. Surprisingly, a minority of publications (n=39) made use of consumer-grade equipment. Lighting conditions were primarily uncontrolled or ambient. While some works focused on specialized aspects such as the removal of vital sign information from video streams to protect privacy or the influence of video compression, most algorithmic developments were related to three areas: region of interest selection, tracking, or extraction of a one-dimensional signal. Seven papers used deep learning techniques, 17 papers used other machine learning approaches, and 92 made no explicit use of machine learning.

CONCLUSION

Although some general trends and frequent shortcomings are obvious, the spectrum of publications related to camera-based vital sign estimation is broad. While many creative solutions and unique approaches exist, the lack of standardization hinders comparability of these techniques and of their performance. We believe that sharing algorithms and/ or datasets will alleviate this and would allow the application of newer techniques such as deep learning.

Hyperspectral imaging of human skin aided by artificial neural networks

We developed a compact, hand-held hyperspectral imaging system for 2D neural network-based visualization of skin chromophores and blood oxygenation. State-of-the-art micro-optic multichannel matrix sensor combined with the tunable Fabry-Perot micro interferometer enables a portable diagnostic device sensitive to the changes of the oxygen saturation as well as the variations of blood volume fraction of human skin. Generalized object-oriented Monte Carlo model is used extensively for the training of an artificial neural network utilized for the hyperspectral image processing. In addition, the results are verified and validated via actual experiments with tissue phantoms and human skin in vivo. The proposed approach enables a tool combining both the speed of an artificial neural network processing and the accuracy and flexibility of advanced Monte Carlo modeling. Finally, the results of the feasibility studies and the experimental tests on biotissue phantoms and healthy volunteers are presented.

Clinical assessment of a non-invasive wearable MEMS pressure sensor array for monitoring of arterial pulse waveform, heart rate and detection of atrial fibrillation

There is an unmet clinical need for a low cost and easy to use wearable devices for continuous cardiovascular health monitoring. A flexible and wearable wristband, based on microelectromechanical sensor (MEMS) elements array was developed to support this need. The performance of the device in cardiovascular monitoring was investigated by (i) comparing the arterial pressure waveform recordings to the gold standard, invasive catheter recording (n = 18), (ii) analyzing the ability to detect irregularities of the rhythm (n = 7), and (iii) measuring the heartrate monitoring accuracy (n = 31). Arterial waveforms carry important physiological information and the comparison study revealed that the recordings made with the wearable device and with the gold standard device resulted in almost identical (r = 0.9–0.99) pulse waveforms. The device can measure the heart rhythm and possible irregularities in it. A clustering analysis demonstrates a perfect classification accuracy between atrial fibrillation (AF) and sinus rhythm. The heartrate monitoring study showed near perfect beat-to-beat accuracy (sensitivity = 99.1%, precision = 100%) on healthy subjects. In contrast, beat-to-beat detection from coronary artery disease patients was challenging, but the averaged heartrate was extracted successfully (95% CI: −1.2 to 1.1 bpm). In conclusion, the results indicate that the device could be useful in remote monitoring of cardiovascular diseases and personalized medicine.

Monte Carlo Analysis of Optical Interactions in Reflectance and Transmittance Finger Photoplethysmography

Photoplethysmography (PPG) is a non-invasive photometric technique that measures the volume changes in arterial blood. Recent studies have reported limitations in developing and optimising PPG-based sensing technologies due to unavailability of the fundamental information such as PPG-pathlength and penetration depth in a certain region of interest (ROI) in the human body. In this paper, a robust computational model of a dual wavelength PPG system was developed using Monte Carlo technique. A three-dimensional heterogeneous volume of a specific ROI (i.e., human finger) was exposed at the red (660 nm) and infrared (940 nm) wavelengths in the reflectance and transmittance modalities of PPG. The optical interactions with the individual pulsatile and non-pulsatile tissue-components were demonstrated and the optical parameters (e.g., pathlength, penetration depth, absorbance, reflectance and transmittance) were investigated. Results optimised the source-detector separation for a reflectance finger-PPG sensor. The analysis with the recorded absorbance, reflectance and transmittance confirmed the maximum and minimum impact of the dermis and bone tissue-layers, respectively, in the formation of a PPG signal. The results presented in the paper provide the necessary information to develop PPG-based transcutaneous sensors and to understand the origin of the ac and dc components of the PPG signal.

Current progress of photoplethysmography and SPO2 for health monitoring

A photoplethysmograph (PPG) is a simple medical device for monitoring blood flow and transportation of substances in the blood. It consists of a light source and a photodetector for measuring transmitted and reflected light signals. Clinically, PPGs are used to monitor the pulse rate, oxygen saturation, blood pressure, and blood vessel stiffness. Wearable unobtrusive PPG monitors are commercially available. Here, we review the principle issues and clinical applications of PPG for monitoring oxygen saturation.

Frame Registration for Motion Compensation in Imaging Photoplethysmography

Imaging photoplethysmography (iPPG) is an emerging technology used to assess microcirculation and cardiovascular signs by collecting backscattered light from illuminated tissue using optical imaging sensors. An engineering approach is used to evaluate whether a silicone cast of a human palm might be effectively utilized to predict the results of image registration schemes for motion compensation prior to their application on live human tissue. This allows us to establish a performance baseline for each of the algorithms and to isolate performance and noise fluctuations due to the induced motion from the temporally changing physiological signs. A multi-stage evaluation model is developed to qualitatively assess the influence of the region of interest (ROI), system resolution and distance, reference frame selection, and signal normalization on extracted iPPG waveforms from live tissue. We conclude that the application of image registration is able to deliver up to 75% signal-to-noise (SNR) improvement (4.75 to 8.34) over an uncompensated iPPG signal by employing an intensity-based algorithm with a moving reference frame.

Contactless monitoring of the blood-flow changes in upper limbs

Vasomotor reactivity, which is important to estimate neurogenic regulation of blood vessels in patients with different pathologies, is still assessed by occlusion plethysmography using sensors contacting the limbs. Recently we proposed a contactless approach for measuring blood flow changes during venous occlusion using imaging photoplethysmography [Kamshilin et al., Sci. Rep.7, 4642017]. In this work, the response of the vascular system on the occlusion was studied simultaneously by contact air-plethysmography system and remote optical system under illumination by incoherent polarized green light. A high correlation (r > 0.93) between the waveforms measured by both system was observed. Moreover, we found that the response of the optical system on the venous occlusion is uniform at the whole area of the forearm. The new optical technique is more convenient for assessment of the blood flow dynamics because it can be used for measurements in any part of the body. Method of imaging photoplethysmography is very promising for use in equipment intended for evaluation of neurogenic mechanisms of regulation of vascular blood flow.

Noninvasive Monitoring of Blood Glucose Using Color-Coded Photoplethysmographic Images of the Illuminated Fingertip Within the Visible and Near-Infrared Range: Opportunities and Questions

Noninvasive blood glucose assays have been promised for many years and various molecular spectroscopy-based methods of skin are candidates for achieving this goal. Due to the small spectral signatures of the glucose used for direct physical detection, moreover hidden among a largely variable background, broad spectral intervals are usually required to provide the mandatory analytical selectivity, but no such device has so far reached the accuracy that is required for self-monitoring of blood glucose (SMBG). A recently presented device as described in this journal, based on photoplethysmographic fingertip images for measuring glucose in a nonspecific indirect manner, is especially evaluated for providing reliable blood glucose concentration predictions.

Comparison of speckleplethysmographic (SPG) and photoplethysmographic (PPG) imaging by Monte Carlo simulations and in vivo measurements

Noncontact photoplethysmography (PPG) is limited by a poor signal-to-noise ratio (SNR). A solution to this limitation is the use of alternate sources of optical contrast to generate a complementary pulsatile waveform. One such source is laser speckle contrast, which is modulated in biological tissues by the flow rate of red blood cells. Averaging a region of interest from a speckle contrast image over time allows for the calculation of a speckleplethysmogram (SPG). Similar to PPG, SPG enables monitoring of heart rate and respiratory rate. A gap in the knowledge base exists as to the precise spatiotemporal relationship between PPG and SPG signals. We have developed an eight-layer tissue model to simulate both PPG and SPG signals in a reflectance geometry via Monte Carlo methods. We modeled PPG by compression of the upper and lower blood nets due to expansion of the larger arterial layer below. The in silico PPG peak-to-peak amplitude percent was greater at 532 nm than at 860 nm (5.6% vs. 3.0%, respectively), which matches trends from the literature. We modeled SPG by changing flow speeds of red blood cells in both the capillaries and arterioles over the cardiac cycle. The in silico SPG peak-to-peak amplitude percent was 24% at 532 nm and 40% at 860 nm. In silico results are similar to in vivo results measured with a two-camera set up for simultaneous imaging of PPG and SPG. Both in silico and in vivo data suggest SPG has a much larger SNR than PPG, which may prove beneficial for noncontact, wide-field optical monitoring of cardiovascular health.